Search results for: Finite Element Modeling

Authors: Ben Khayut, Lina Fabri, Maya Avikhana

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The modern Artificial Narrow Intelligence (ANI) models cannot: a) independently, situationally, and continuously function without of human intelligence, used for retraining and reprogramming the ANI’s models, and b) think, understand, be conscious, and cognize under uncertainty and changing of the environmental objects. To eliminate these shortcomings and build a new generation of Artificial Intelligence systems, the paper proposes a Conception, Model, and Method of Computational Psycholinguistic Cognitive Situational-Fuzzy Self-Controlled Brain and Mind System (CPCSFSCBMSUU). This system uses a neural network as its computational memory, and activates functions of the perception, identification of real objects, fuzzy situational control, and forming images of these objects. These images and objects are used for modeling their psychological, linguistic, cognitive, and neural values of properties and features, the meanings of which are identified, interpreted, generated, and formed taking into account the identified subject area, using the data, information, knowledge, accumulated in the Memory. The functioning of the CPCSFSCBMSUU is carried out by its subsystems of the: fuzzy situational control of all processes, computational perception, identifying of reactions and actions, Psycholinguistic Cognitive Fuzzy Logical Inference, Decision Making, Reasoning, Systems Thinking, Planning, Awareness, Consciousness, Cognition, Intuition, and Wisdom. In doing so are performed analysis and processing of the psycholinguistic, subject, visual, signal, sound and other objects, accumulation and using the data, information and knowledge of the Memory, communication, and interaction with other computing systems, robots and humans in order of solving the joint tasks. To investigate the functional processes of the proposed system, the principles of situational control, fuzzy logic, psycholinguistics, informatics, and modern possibilities of data science were applied. The proposed self-controlled system of brain and mind is oriented on use as a plug-in in multilingual subject applications.

Keywords: Computational psycholinguistic cognitive brain and mind system, situational fuzzy control, uncertainty, AI.

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Authors: Francis William S, Imtiaz Ahmed Choudhury, Ananda Kumar Eriki, A. John Rajan

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Diesel Engines emit complex mixtures of inorganic and organic compounds in the form of both solid and vapour phase particles. Most of the particulates released are ultrafine nanoparticles which are detrimental to human health and can easily enter the body by respiration. The emissions standards on particulate matter release from diesel engines are constantly upgraded within the European Union and with future regulations based on the particles numbers released instead of merely mass, the need for effective aftertreatment devices will increase. Standard particulate filters in the form of wall flow filters can have problems with high soot accumulation, producing a large exhaust backpressure. A potential solution would be to combine the standard filter with a flow through filter to reduce the load on the wall flow filter. In this paper soot particle trapping has been simulated in different continuous flow filters of monolithic structure including the use of promoters, at laminar flow conditions. An Euler Lagrange model, the discrete phase model in Ansys used with user defined functions for forces acting on particles. A method to quickly screen trapping of 5 nm and 10 nm particles in different catalysts designs with tracers was also developed. Simulations of square duct monoliths with promoters show that the strength of the vortices produced are not enough to give a high amount of particle deposition on the catalyst walls. The smallest particles in the simulations, 5 and 10 nm particles were trapped to a higher extent, than larger particles up to 1000 nm, in all studied geometries with the predominant deposition mechanism being Brownian diffusion. The comparison of the different filters designed with a wall flow filter does show that the options for altering a design of a flow through filter, without imposing a too large pressure drop penalty are good.

Keywords: Diesel Engine trap, thermophoresis, Exhaust pipe, PM-Simulation modeling.

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Authors: R. Sekula

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Epoxy composites are broadly used as an electrical insulation for the high voltage applications since only such materials can fulfill particular mechanical, thermal, and dielectric requirements. However, properties of the final product are strongly dependent on proper manufacturing process with minimized material failures, as too large shrinkage, voids and cracks. Therefore, application of proper materials (epoxy, hardener, and filler) and process parameters (mold temperature, filling time, filling velocity, initial temperature of internal parts, gelation time), as well as design and geometric parameters are essential features for final quality of the produced components. In this paper, an approach for three-dimensional modeling of all molding stages, namely filling, curing and post-curing is presented. The reactive molding simulation tool is based on a commercial CFD package, and include dedicated models describing viscosity and reaction kinetics that have been successfully implemented to simulate the reactive nature of the system with exothermic effect. Also a dedicated simulation procedure for stress and shrinkage calculations, as well as simulation results are presented in the paper. Second part of the paper is dedicated to recent developments on formulations of functional composites for electrical insulation applications, focusing on thermally conductive materials. Concepts based on filler modifications for epoxy electrical composites have been presented, including the results of the obtained properties. Finally, having in mind tough environmental regulations, in addition to current process and design aspects, an approach for product re-design has been presented focusing on replacement of epoxy material with the thermoplastic one. Such “design-for-recycling” method is one of new directions associated with development of new material and processing concepts of electrical products and brings a lot of additional research challenges. For that, one of the successful products has been presented to illustrate the presented methodology.

Keywords: Curing, epoxy insulation, numerical simulations, recycling.

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Authors: P. Mounnarath, U. Schmitz, Ch. Zhang

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Fragility analysis is an effective tool for the seismic vulnerability assessment of civil structures in the last several years. The design of the expansion joints according to various bridge design codes is almost inconsistent, and only a few studies have focused on this problem so far. In this study, the influence of the expansion joint clearances between the girder ends and the abutment backwalls on the seismic fragility assessment of continuous integral bridge frames is investigated. The gaps (ranging from 60 mm, 150 mm, 250 mm and 350 mm) are designed by following two different bridge design code specifications, namely, Caltrans and Eurocode 8-2. Five bridge models are analyzed and compared. The first bridge model serves as a reference. This model uses three-dimensional reinforced concrete fiber beam-column elements with simplified supports at both ends of the girder. The other four models also employ reinforced concrete fiber beam-column elements but include the abutment backfill stiffness and four different gap values. The nonlinear time history analysis is performed. The artificial ground motion sets, which have the peak ground accelerations (PGAs) ranging from 0.1 g to 1.0 g with an increment of 0.05 g, are taken as input. The soil-structure interaction and the P-Δ effects are also included in the analysis. The component fragility curves in terms of the curvature ductility demand to the capacity ratio of the piers and the displacement demand to the capacity ratio of the abutment sliding bearings are established and compared. The system fragility curves are then obtained by combining the component fragility curves. Our results show that in the component fragility analysis, the reference bridge model exhibits a severe vulnerability compared to that of other sophisticated bridge models for all damage states. In the system fragility analysis, the reference curves illustrate a smaller damage probability in the earlier PGA ranges for the first three damage states, they then show a higher fragility compared to other curves in the larger PGA levels. In the fourth damage state, the reference curve has the smallest vulnerability. In both the component and the system fragility analysis, the same trend is found that the bridge models with smaller clearances exhibit a smaller fragility compared to that with larger openings. However, the bridge model with a maximum clearance still induces a minimum pounding force effect.

Keywords: Expansion joint clearance, fiber beam-column element, fragility assessment, time history analysis.

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Authors: Angelo Corallo, Maria Elena Latino, Marta Menegoli

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Agri-food value chain involves various stakeholders with different roles. All of them abide by national and international rules and leverage marketing strategies to advance their products. Food products and related processing phases carry with it a big mole of data that are often not used to inform final customer. Some data, if fittingly identified and used, can enhance the single company, and/or the all supply chain creates a math between marketing techniques and voluntary traceability strategies. Moreover, as of late, the world has seen buying-models’ modification: customer is careful on wellbeing and food quality. Food citizenship and food democracy was born, leveraging on transparency, sustainability and food information needs. Internet of Things (IoT) and Analytics, some of the innovative technologies of Industry 4.0, have a significant impact on market and will act as a main thrust towards a genuine ‘4.0 change’ for agriculture. But, realizing a traceability system is not simple because of the complexity of agri-food supply chain, a lot of actors involved, different business models, environmental variations impacting products and/or processes, and extraordinary climate changes. In order to give support to the company involved in a traceability path, starting from business model analysis and related business process a Framework to Manage Product Data in Agri-Food Supply Chain for Voluntary Traceability was conceived. Studying each process task and leveraging on modeling techniques lead to individuate information held by different actors during agri-food supply chain. IoT technologies for data collection and Analytics techniques for data processing supply information useful to increase the efficiency intra-company and competitiveness in the market. The whole information recovered can be shown through IT solutions and mobile application to made accessible to the company, the entire supply chain and the consumer with the view to guaranteeing transparency and quality.

Keywords: Agriculture 4.0, agri-food supply chain, Industry 4.0, voluntary traceability.

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Authors: Jalal Haghighat Monfared, Zahra Akbari

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Today, business executives need to have useful information to make better decisions. Banks have also been using information tools so that they can direct the decision-making process in order to achieve their desired goals by rapidly extracting information from sources with the help of business intelligence. The research seeks to investigate whether there is a relationship between the quality of decision making and the business intelligence capabilities of Mellat Bank. Each of the factors studied is divided into several components, and these and their relationships are measured by a questionnaire. The statistical population of this study consists of all managers and experts of Mellat Bank's General Departments (including 190 people) who use commercial intelligence reports. The sample size of this study was 123 randomly determined by statistical method. In this research, relevant statistical inference has been used for data analysis and hypothesis testing. In the first stage, using the Kolmogorov-Smirnov test, the normalization of the data was investigated and in the next stage, the construct validity of both variables and their resulting indexes were verified using confirmatory factor analysis. Finally, using the structural equation modeling and Pearson's correlation coefficient, the research hypotheses were tested. The results confirmed the existence of a positive relationship between decision quality and business intelligence capabilities in Mellat Bank. Among the various capabilities, including data quality, correlation with other systems, user access, flexibility and risk management support, the flexibility of the business intelligence system was the most correlated with the dependent variable of the present research. This shows that it is necessary for Mellat Bank to pay more attention to choose the required business intelligence systems with high flexibility in terms of the ability to submit custom formatted reports. Subsequently, the quality of data on business intelligence systems showed the strongest relationship with quality of decision making. Therefore, improving the quality of data, including the source of data internally or externally, the type of data in quantitative or qualitative terms, the credibility of the data and perceptions of who uses the business intelligence system, improves the quality of decision making in Mellat Bank.

Keywords: Business intelligence, business intelligence capability, decision making, decision quality.

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Authors: Antonio Vitale, Nicola Genito, Giovanni Cuciniello, Ferdinando Montemari

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The introduction of tilt-rotor aircraft into the existing civilian air transportation system will provide beneficial effects due to tilt-rotor capability to combine the characteristics of a helicopter and a fixed-wing aircraft into one vehicle. The disposability of reliable tilt-rotor simulation models supports the development of such vehicle. Indeed, simulation models are required to design automatic control systems that increase safety, reduce pilot's workload and stress, and ensure the optimal aircraft configuration with respect to flight envelope limits, especially during the most critical flight phases such as conversion from helicopter to aircraft mode and vice versa. This article presents a process to build a simplified tilt-rotor simulation model, derived from the analysis of flight data. The model aims to reproduce the complex dynamics of tilt-rotor during the in-flight conversion phase. It uses a set of scheduled linear transfer functions to relate the autopilot reference inputs to the most relevant rigid body state variables. The model also computes information about the rotor flapping dynamics, which are useful to evaluate the aircraft control margin in terms of rotor collective and cyclic commands. The rotor flapping model is derived through a mixed theoretical-empirical approach, which includes physical analytical equations (applicable to helicopter configuration) and parametric corrective functions. The latter are introduced to best fit the actual rotor behavior and balance the differences existing between helicopter and tilt-rotor during flight. Time-domain system identification from flight data is exploited to optimize the model structure and to estimate the model parameters. The presented model-building process was applied to simulated flight data of the ERICA Tilt-Rotor, generated by using a high fidelity simulation model implemented in FlightLab environment. The validation of the obtained model was very satisfying, confirming the validity of the proposed approach.

Keywords: Flapping Dynamics, Flight Dynamics, System Identification, Tilt-Rotor Modeling and Simulation.

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Authors: Anjali Sadanand, R. V. Nagarajan

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Architecture morphs with advances in technology and the roof, wall, and floor as basic elements of a building, follow in redefining themselves over time. Their contribution is bound by time and held by design principles that deal with function, sturdiness, and beauty. Architecture engages with people to give joy through its form, material, design structure, and spatial qualities. This paper attempts to re-interpret John Ruskin’s “Seven lamps of Architecture” in the context of the architecture of the modern and present period. The paper focuses on the “wall” as an element of study in this context. Four of Ruskin’s seven lamps will be discussed, namely beauty, truth, life, and memory, through examples of architecture ranging from modernism to contemporary architecture of today. The study will focus on the relevance of Ruskin’s principles to the “wall” in specific, in buildings of different materials and over a range of typologies from all parts of the world. Two examples will be analyzed for each lamp. It will be shown that in each case, there is relevance to the significance of Ruskin’s lamps in modern and contemporary architecture. Nature to which Ruskin alludes to for his lamp of “beauty” is found in the different expressions of interpretation used by Corbusier in his Villa Stein façade based on proportion found in nature and in the direct expression of Toyo Ito in his translation of an understanding of the structure of trees into his façade design of the showroom for a Japanese bag boutique. “Truth” is shown in Mies van der Rohe’s Crown Hall building with its clarity of material and structure and Studio Mumbai’s Palmyra House, which celebrates the use of natural materials and local craftsmanship. “Life” is reviewed with a sustainable house in Kerala by Ashrams Ravi and Alvar Aalto’s summer house, which illustrate walls as repositories of intellectual thought and craft. “Memory” is discussed with Charles Correa’s Jawahar Kala Kendra and Venturi’s Vana Venturi house and discloses facades as text in the context of its materiality and iconography. Beauty is reviewed in Villa Stein and Toyo Ito’s Branded Retail building in Tokyo. The paper thus concludes that Ruskin’s Lamps can be interpreted in today’s context and add richness to meaning to the understanding of architecture.

Keywords: Beauty, design, façade, modernism.

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Authors: Wojciech Górecki, Anna Sowiżdżał, Grzegorz Machowski, Tomasz Maćkowski, Bartosz Papiernik, Michał Stefaniuk

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The article shows results of the project which aims at evaluating possibilities of effective development and exploitation of natural gas from argillaceous series of the Autochthonous Miocene in the Carpathian Foredeep. To achieve the objective, the research team develop a world-trend based but unique methodology of processing and interpretation, adjusted to data, local variations and petroleum characteristics of the area. In order to determine the zones in which maximum volumes of hydrocarbons might have been generated and preserved as shale gas reservoirs, as well as to identify the most preferable well sites where largest gas accumulations are anticipated a number of task were accomplished. Evaluation of petrophysical properties and hydrocarbon saturation of the Miocene complex is based on laboratory measurements as well as interpretation of well-logs and archival data. The studies apply mercury porosimetry (MICP), micro CT and nuclear magnetic resonance imaging (using the Rock Core Analyzer). For prospective location (e.g. central part of Carpathian Foredeep – Brzesko-Wojnicz area) reprocessing and reinterpretation of detailed seismic survey data with the use of integrated geophysical investigations has been made. Construction of quantitative, structural and parametric models for selected areas of the Carpathian Foredeep is performed on the basis of integrated, detailed 3D computer models. Modeling are carried on with the Schlumberger’s Petrel software. Finally, prospective zones are spatially contoured in a form of regional 3D grid, which will be framework for generation modelling and comprehensive parametric mapping, allowing for spatial identification of the most prospective zones of unconventional gas accumulation in the Carpathian Foredeep. Preliminary results of research works indicate a potentially prospective area for occurrence of unconventional gas accumulations in the Polish part of Carpathian Foredeep.

Keywords: Autochthonous Miocene, Carpathian Foredeep, Poland, shale gas.

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Authors: Addin Osman, Anwar Ali Yahya, Mohammed Basit Kamal

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Datasets or collections are becoming important assets by themselves and now they can be accepted as a primary intellectual output of a research. The quality and usage of the datasets depend mainly on the context under which they have been collected, processed, analyzed, validated, and interpreted. This paper aims to present a collection of program educational objectives mapped to student’s outcomes collected from self-study reports prepared by 32 engineering programs accredited by ABET. The manual mapping (classification) of this data is a notoriously tedious, time consuming process. In addition, it requires experts in the area, which are mostly not available. It has been shown the operational settings under which the collection has been produced. The collection has been cleansed, preprocessed, some features have been selected and preliminary exploratory data analysis has been performed so as to illustrate the properties and usefulness of the collection. At the end, the collection has been benchmarked using nine of the most widely used supervised multiclass classification techniques (Binary Relevance, Label Powerset, Classifier Chains, Pruned Sets, Random k-label sets, Ensemble of Classifier Chains, Ensemble of Pruned Sets, Multi-Label k-Nearest Neighbors and Back-Propagation Multi-Label Learning). The techniques have been compared to each other using five well-known measurements (Accuracy, Hamming Loss, Micro-F, Macro-F, and Macro-F). The Ensemble of Classifier Chains and Ensemble of Pruned Sets have achieved encouraging performance compared to other experimented multi-label classification methods. The Classifier Chains method has shown the worst performance. To recap, the benchmark has achieved promising results by utilizing preliminary exploratory data analysis performed on the collection, proposing new trends for research and providing a baseline for future studies.

Keywords: Benchmark collection, program educational objectives, student outcomes, ABET, Accreditation, machine learning, supervised multiclass classification, text mining.

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Authors: Yuri Boiko, Iluju Kiringa, Tet Yeap

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Current drainage attack suggested previously is further studied in regular settings of closed-loop controlled Brushless DC (BLDC) motor with Kalman filter in the feedback loop. Modeling and simulation experiments are conducted in a MATLAB environment, implementing the closed-loop control model of BLDC motor operation in position sensorless mode under Kalman filter drive. The current increase in the motor windings is caused by the controller (p-controller in our case) affected by false data injection of substitution of the angular velocity estimates with distorted values. Operation of multiplication to distortion coefficient, values of which are taken from the distortion function synchronized in its periodicity with the rotor’s position change. A saw function with a triangular tooth shape is studied herewith for the purpose of carrying out the bias injection with current drainage consequences. The specific focus here is on how the asymmetry of the tooth in the saw function affects the flow of current drainage. The purpose is two-fold: (i) to produce and collect the signature of an asymmetric saw in the attack for further pattern recognition process, and (ii) to determine conditions of improving stealthiness of such attack via regulating asymmetry in saw function used. It is found that modification of the symmetry in the saw tooth affects the periodicity of current drainage modulation. Specifically, the modulation frequency of the drained current for a fully asymmetric tooth shape coincides with the saw function modulation frequency itself. Increasing the symmetry parameter for the triangle tooth shape leads to an increase in the modulation frequency for the drained current. Moreover, such frequency reaches the switching frequency of the motor windings for fully symmetric triangular shapes, thus becoming undetectable and improving the stealthiness of the attack. Therefore, the collected signatures of the attack can serve for attack parameter identification via the pattern recognition route.

Keywords: Bias injection attack, Kalman filter, BLDC motor, control system, closed loop, P-controller, PID-controller, current drainage, saw-function, asymmetry.

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Authors: Elnaz Saeedi, Jamileh Abolaghasemi, Mohsen Nasiri Tousi, Saeedeh Khosravi

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Goals and Objectives: A typical analysis of survival data involves the modeling of time-to-event data, such as the time till death. A frailty model is a random effect model for time-to-event data, where the random effect has a multiplicative influence on the baseline hazard function. This article aims to investigate the use of gamma frailty model with concomitant variable in order to individualize the prognostic factors that influence the liver cirrhosis patients’ survival times. Methods: During the one-year study period (May 2008-May 2009), data have been used from the recorded information of patients with liver cirrhosis who were scheduled for liver transplantation and were followed up for at least seven years in Imam Khomeini Hospital in Iran. In order to determine the effective factors for cirrhotic patients’ survival in the presence of latent variables, the gamma frailty distribution has been applied. In this article, it was considering the parametric model, such as Exponential and Weibull distributions for survival time. Data analysis is performed using R software, and the error level of 0.05 was considered for all tests. Results: 305 patients with liver cirrhosis including 180 (59%) men and 125 (41%) women were studied. The age average of patients was 39.8 years. At the end of the study, 82 (26%) patients died, among them 48 (58%) were men and 34 (42%) women. The main cause of liver cirrhosis was found hepatitis 'B' with 23%, followed by cryptogenic with 22.6% were identified as the second factor. Generally, 7-year’s survival was 28.44 months, for dead patients and for censoring was 19.33 and 31.79 months, respectively. Using multi-parametric survival models of progressive and regressive, Exponential and Weibull models with regard to the gamma frailty distribution were fitted to the cirrhosis data. In both models, factors including, age, bilirubin serum, albumin serum, and encephalopathy had a significant effect on survival time of cirrhotic patients. Conclusion: To investigate the effective factors for the time of patients’ death with liver cirrhosis in the presence of latent variables, gamma frailty model with parametric distributions seems desirable.

Keywords: Frailty model, latent variables, liver cirrhosis, parametric distribution.

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Authors: I. Lucas, N. Schomberg, F-A. Couturier

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Most empirical studies have analyzed how liquidity risks faced by individual institutions turn into systemic risk. Recent banking crisis has highlighted the importance of grasping and controlling the systemic risk, and the acceptance by Central Banks to ease their monetary policies for saving default or illiquid banks. This last point shows that banks would pay less attention to liquidity risk which, in turn, can become a new important channel of loss. The financial regulation focuses on the most important and “systemic” banks in the global network. However, to quantify the expected loss associated with liquidity risk, it is worth to analyze sensitivity to this channel for the various elements of the global bank network. A small bank is not considered as potentially systemic; however the interaction of small banks all together can become a systemic element. This paper analyzes the impact of medium and small banks interaction on a set of banks which is considered as the core of the network. The proposed method uses the structure of agent-based model in a two-class environment. In first class, the data from actual balance sheets of 22 large and systemic banks (such as BNP Paribas or Barclays) are collected. In second one, to model a network as closely as possible to actual interbank market, 578 fictitious banks smaller than the ones belonging to first class have been split into two groups of small and medium ones. All banks are active on the European interbank network and have deposit and market activity. A simulation of 12 three month periods representing a midterm time interval three years is projected. In each period, there is a set of behavioral descriptions: repayment of matured loans, liquidation of deposits, income from securities, collection of new deposits, new demands of credit, and securities sale. The last two actions are part of refunding process developed in this paper. To strengthen reliability of proposed model, random parameters dynamics are managed with stochastic equations as rates the variations of which are generated by Vasicek model. The Central Bank is considered as the lender of last resort which allows banks to borrow at REPO rate and some ejection conditions of banks from the system are introduced.

Liquidity crunch due to exogenous crisis is simulated in the first class and the loss impact on other bank classes is analyzed though aggregate values representing the aggregate of loans and/or the aggregate of borrowing between classes. It is mainly shown that the three groups of European interbank network do not have the same response, and that intermediate banks are the most sensitive to liquidity risk.

Keywords: Systemic Risk, Financial Contagion, Liquidity Risk, Interbank Market, Network Model.

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Authors: A. Soria-Salinas, M.-P. Zorzano, J. Martín-Torres, J. Sánchez-García-Casarrubios, J.-L. Pérez-Díaz, A. Vakkada-Ramachandran

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The current state-of-the-art methods of mass gauging of Electric Propulsion (EP) propellants in microgravity conditions rely on external measurements that are taken at the surface of the tank. The tanks are operated under a constant thermal duty cycle to store the propellant within a pre-defined temperature and pressure range. We demonstrate using computational fluid dynamics (CFD) simulations that the heat-transfer within the pressurized propellant generates temperature and density anisotropies. This challenges the standard mass gauging methods that rely on the use of time changing skin-temperatures and pressures. We observe that the domes of the tanks are prone to be overheated, and that a long time after the heaters of the thermal cycle are switched off, the system reaches a quasi-equilibrium state with a more uniform density. We propose a new gauging method, which we call the Improved PVT method, based on universal physics and thermodynamics principles, existing TRL-9 technology and telemetry data. This method only uses as inputs the temperature and pressure readings of sensors externally attached to the tank. These sensors can operate during the nominal thermal duty cycle. The improved PVT method shows little sensitivity to the pressure sensor drifts which are critical towards the end-of-life of the missions, as well as little sensitivity to systematic temperature errors. The retrieval method has been validated experimentally with CO₂ in gas and fluid state in a chamber that operates up to 82 bar within a nominal thermal cycle of 38 °C to 42 °C. The mass gauging error is shown to be lower than 1% the mass at the beginning of life, assuming an initial tank load at 100 bar. In particular, for a pressure of about 70 bar, just below the critical pressure of CO₂, the error of the mass gauging in gas phase goes down to 0.1% and for 77 bar, just above the critical point, the error of the mass gauging of the liquid phase is 0.6% of initial tank load. This gauging method improves by a factor of 8 the accuracy of the standard PVT retrievals using look-up tables with tabulated data from the National Institute of Standards and Technology.

Keywords: Electric propulsion, mass gauging, propellant, PVT, xenon.

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Authors: Rajinder Singh, Ram Valluru

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Chain Ladder (CL) method, Expected Loss Ratio (ELR) method and Bornhuetter-Ferguson (BF) method, in addition to more complex transition-rate modeling, are commonly used actuarial reserving methods in general insurance. There is limited published research about their relative performance in the context of Mortgage Insurance (MI). In our experience, these traditional techniques pose unique challenges and do not provide stable claim estimates for medium to longer term liabilities. The relative strengths and weaknesses among various alternative approaches revolve around: stability in the recent loss development pattern, sufficiency and reliability of loss development data, and agreement/disagreement between reported losses to date and ultimate loss estimate. CL method results in volatile reserve estimates, especially for accident periods with little development experience. The ELR method breaks down especially when ultimate loss ratios are not stable and predictable. While the BF method provides a good tradeoff between the loss development approach (CL) and ELR, the approach generates claim development and ultimate reserves that are disconnected from the ever-to-date (ETD) development experience for some accident years that have more development experience. Further, BF is based on subjective a priori assumption. The fundamental shortcoming of these methods is their inability to model exogenous factors, like the economy, which impact various cohorts at the same chronological time but at staggered points along their life-time development. This paper proposes an alternative approach of parametrizing the loss development curve and using logistic regression to generate the ultimate loss estimate for each homogeneous group (accident year or delinquency period). The methodology was tested on an actual MI claim development dataset where various cohorts followed a sigmoidal trend, but levels varied substantially depending upon the economic and operational conditions during the development period spanning over many years. The proposed approach provides the ability to indirectly incorporate such exogenous factors and produce more stable loss forecasts for reserving purposes as compared to the traditional CL and BF methods.

Keywords: Actuarial loss reserving techniques, logistic regression, parametric function, volatility.

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Authors: A. D'Alessandro, F. Ubertini, A. L. Materazzi

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In the field of civil engineering, Structural Health Monitoring is a topic of growing interest. Effective monitoring instruments permit the control of the working conditions of structures and infrastructures, through the identification of behavioral anomalies due to incipient damages, especially in areas of high environmental hazards as earthquakes. While traditional sensors can be applied only in a limited number of points, providing a partial information for a structural diagnosis, novel transducers may allow a diffuse sensing. Thanks to the new tools and materials provided by nanotechnology, new types of multifunctional sensors are developing in the scientific panorama. In particular, cement-matrix composite materials capable of diagnosing their own state of strain and tension, could be originated by the addition of specific conductive nanofillers. Because of the nature of the material they are made of, these new cementitious nano-modified transducers can be inserted within the concrete elements, transforming the same structures in sets of widespread sensors. This paper is aimed at presenting the results of a research about a new self-sensing nanocomposite and about the implementation of smart sensors for Structural Health Monitoring. The developed nanocomposite has been obtained by inserting multi walled carbon nanotubes within a cementitious matrix. The insertion of such conductive carbon nanofillers provides the base material with piezoresistive characteristics and peculiar sensitivity to mechanical modifications. The self-sensing ability is achieved by correlating the variation of the external stress or strain with the variation of some electrical properties, such as the electrical resistance or conductivity. Through the measurement of such electrical characteristics, the performance and the working conditions of an element or a structure can be monitored. Among conductive carbon nanofillers, carbon nanotubes seem to be particularly promising for the realization of self-sensing cement-matrix materials. Some issues related to the nanofiller dispersion or to the influence of the nano-inclusions amount in the cement matrix need to be carefully investigated: the strain sensitivity of the resulting sensors is influenced by such factors. This work analyzes the dispersion of the carbon nanofillers, the physical properties of the fresh dough, the electrical properties of the hardened composites and the sensing properties of the realized sensors. The experimental campaign focuses specifically on their dynamic characterization and their applicability to the monitoring of full-scale elements. The results of the electromechanical tests with both slow varying and dynamic loads show that the developed nanocomposite sensors can be effectively used for the health monitoring of structures.

Keywords: Carbon nanotubes, self-sensing nanocomposites, smart cement-matrix sensors, structural health monitoring.

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Authors: Carmiña L. Vargas-Zapata, María A. Conde-Sarmiento, Maria Consuelo Maestre-Vargas

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Calcium is an essential element for good growth and development of the organism, and its requirement is increased at school age. Low socio-economic populations of developing countries such as Colombia may have food deficiency of this mineral in schoolchildren that could be reflected in calcium biochemical indicators, bone alterations and anthropometric indicators. The objective of this investigation was to evaluate some calcium biochemical indicators in a group of schoolchildren of low socioeconomic level from Barranquilla city and to correlate with body mass index. 60 schoolchildren aged 7 to 15 years were selected from Jesus’s Heart Educational Institution in Barranquilla-Atlántico, apparently healthy, without suffering from infectious or gastrointestinal diseases, without habits of drinking alcohol or smoking another hallucinogenic substance and without taking supplementation with calcium in the last six months or another substance that compromises bone metabolism. The research was approved by the ethics committee at Universidad del Atlántico. The selected children were invited to donate a blood and urine sample in a fasting time of 12 hours, the serum was separated by centrifugation and frozen at ˗20 ℃ until analyzed and the same was done with the urine sample. On the day of the biological collections, the weight and height of the students were measured to determine the nutritional status by BMI using the WHO tables. Calcium concentrations in serum and urine (SCa, UCa), alkaline phosphatase activity total and of bone origin (SAPT, SBAP) and urinary creatinine (UCr) were determined by spectrophotometric methods using commercial kits. Osteocalcin and Cross-linked N-telopeptides of type I collagen (NTx-1) in serum were measured with an enzyme-linked inmunosorbent assay. For statistical analysis the Statgraphics software Centurium XVII was used. 63% (n = 38) and 37% (n = 22) of the participants were male and female, respectively. 78% (n = 47), 5% (n = 3) and 17% (n = 10) had a normal, malnutrition and high nutritional status, respectively. The averages of evaluated indicators levels were (mean ± SD): 9.50 ± 1.06 mg/dL for SCa; 181.3 ± 64.3 U/L for SAPT, 143.8 ± 73.9 U/L for SBAP; 9.0 ± 3.48 ng/mL for osteocalcin and 101.3 ± 12.8 ng/mL for NTx-1. UCa level was 12.8 ± 7.7 mg/dL that adjusted with creatinine ranged from 0.005 to 0.395 mg/mg. Considering serum calcium values, approximately 7% of school children were hypocalcemic, 16% hypercalcemic and 77% normocalcemic. The indicators evaluated did not correlate with the BMI. Low values ​​were observed in calcium urinary excretion and high in NTx-1, suggesting that mechanisms such as increase in renal retention of calcium and in bone remodeling may be contributing to calcium homeostasis.

Keywords: Calcium, calcium biochemical, indicators, school children, low socioeconomic status.

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Authors: E. L. Suarez, D. E. Meeroff, Y. Yong

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Current flooding risk modeling focuses on resilience, defined as the probability of recovery from a severe flooding event. However, the long-term damage to property and well-being by nuisance flooding and its long-term effects on communities are not typically included in risk assessments. An approach was developed to address the probability of recovering from a severe flooding event combined with the probability of community performance during a nuisance event. A consolidated model, namely the conflation flooding recovery (&FR) model, evaluates risk-coping mitigation strategies for communities based on the recovery time from catastrophic events, such as hurricanes or extreme surges, and from everyday nuisance flooding events. The &FR model assesses the variation contribution of each independent input and generates a weighted output that favors the distribution with minimum variation. This approach is especially useful if the input distributions have dissimilar variances. The &FR is defined as a single distribution resulting from the product of the individual probability density functions. The resulting conflated distribution resides between the parent distributions, and it infers the recovery time required by a community to return to basic functions, such as power, utilities, transportation, and civil order, after a flooding event. The &FR model is more accurate than averaging individual observations before calculating the mean and variance or averaging the probabilities evaluated at the input values, which assigns the same weighted variation to each input distribution. The main disadvantage of these traditional methods is that the resulting measure of central tendency is exactly equal to the average of the input distribution’s means without the additional information provided by each individual distribution variance. When dealing with exponential distributions, such as resilience from severe flooding events and from nuisance flooding events, conflation results are equivalent to the weighted least squares method or best linear unbiased estimation. The combination of severe flooding risk with nuisance flooding improves flood risk management for highly populated coastal communities, such as in South Florida, USA, and provides a method to estimate community flood recovery time more accurately from two different sources, severe flooding events and nuisance flooding events.

Keywords: Community resilience, conflation, flood risk, nuisance flooding.

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Authors: Jožef Ritonja

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The biochemical industry is one of the most important modern industries. Biochemical reactors are crucial devices of the biochemical industry. The essential bioprocess carried out in bioreactors is the fermentation process. A thorough insight into the fermentation process and the knowledge how to control it are essential for effective use of bioreactors to produce high quality and quantitatively enough products. The development of the control system starts with the determination of a mathematical model that describes the steady state and dynamic properties of the controlled plant satisfactorily, and is suitable for the development of the control system. The paper analyses the fermentation process in bioreactors thoroughly, using existing mathematical models. Most existing mathematical models do not allow the design of a control system for controlling the fermentation process in batch bioreactors. Due to this, a mathematical model was developed and presented that allows the development of a control system for batch bioreactors. Based on the developed mathematical model, a control system was designed to ensure optimal response of the biochemical quantities in the fermentation process. Due to the time-varying and non-linear nature of the controlled plant, the conventional control system with a proportional-integral-differential controller with constant parameters does not provide the desired transient response. The improved adaptive control system was proposed to improve the dynamics of the fermentation. The use of the adaptive control is suggested because the parameters’ variations of the fermentation process are very slow. The developed control system was tested to produce dairy products in the laboratory bioreactor. A carbon dioxide concentration was chosen as the controlled variable. The carbon dioxide concentration correlates well with the other, for the quality of the fermentation process in significant quantities. The level of the carbon dioxide concentration gives important information about the fermentation process. The obtained results showed that the designed control system provides minimum error between reference and actual values of carbon dioxide concentration during a transient response and in a steady state. The recommended control system makes reference signal tracking much more efficient than the currently used conventional control systems which are based on linear control theory. The proposed control system represents a very effective solution for the improvement of the milk fermentation process.

Keywords: Bioprocess engineering, biochemical reactor, fermentation process, modeling, adaptive control.

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Authors: N. Mirzaei Varzeghani, M. Saffarzadeh, A. Naderan, A. Taheri

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Countries are progressing, and the world's busiest airports see year-on-year increases in travel demand. Passenger acceptability of an airport depends on the airport's appeals, which may include one of these routes between the city and the airport, as well as the facilities to reach them. One of the critical roles of transportation planners is to predict future transportation demand so that an integrated, multi-purpose system can be provided and diverse modes of transportation (rail, air, and land) can be delivered to a destination like an airport. In this study, 356 questionnaires were filled out in person over six days. First, the attraction of business and non-business trips was studied using data and a linear regression model. Lower travel costs, more passengers aged 55 and older using this airport, and other factors are essential for business trips. Non-business travelers, on the other hand, have prioritized using personal vehicles to get to the airport and ensuring convenient access to the airport. Business travelers are also less price-sensitive than non-business travelers regarding airport travel. Furthermore, carrying additional luggage (for example, more than one suitcase per person) undoubtedly decreases the attractiveness of public transit. Afterward, based on the manner and purpose of the trip, the locations with the highest trip generation to the airport were identified. The most famous district in Tehran was District 2, with 23 visits, while the most popular mode of transportation was an online taxi, with 12 trips from that location. Then, significant variables in separation and behavior of travel methods to access the airport were investigated for all systems. In this scenario, the most crucial factor is the time it takes to get to the airport, followed by the method's user-friendliness as a component of passenger preference. It has also been demonstrated that enhancing public transportation trip times reduces private transportation's market share, including taxicabs. Based on the responses of personal and semi-public vehicles, the desire of passengers to approach the airport via public transportation systems was explored to enhance present techniques and develop new strategies for providing the most efficient modes of transportation. Using the binary model, it was clear that business travelers and people who had already driven to the airport were the least likely to change.

Keywords: Multimodal transportation, travel behavior, demand modeling, statistical models.

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Authors: Damien Gondre, Hatem Ben Maad, Abdelkrim Trabelsi, Frédéric Kuznik, Joseph Virgone

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The use of a radiant cooling solution would enable to lower cooling needs which is of great interest when the demand is initially high (hot climate). But, radiant systems are not naturally compatibles with humid climates since a low-temperature surface leads to condensation risks as soon as the surface temperature is close to or lower than the dew point temperature. A radiant cooling system combined to a dehumidification system would enable to remove humidity for the space, thereby lowering the dew point temperature. The humidity removal needs to be especially effective near the cooled surface. This requirement could be fulfilled by a system using a single desiccant fluid for the removal of both excessive heat and moisture. This task aims at providing an estimation of the specification requirements of such system in terms of cooling power and dehumidification rate required to fulfill comfort issues and to prevent any condensation risk on the cool panel surface. The present paper develops a preliminary study on the specification requirements, performances and behavior of a combined dehumidifier/cooling ceiling panel for different operating conditions. This study has been carried using the TRNSYS software which allows nodal calculations of thermal systems. It consists of the dynamic modeling of heat and vapor balances of a 5m x 3m x 2.7m office space. In a first design estimation, this room is equipped with an ideal heating, cooling, humidification and dehumidification system so that the room temperature is always maintained in between 21^◦C and 25^◦C with a relative humidity in between 40% and 60%. The room is also equipped with a ventilation system that includes a heat recovery heat exchanger and another heat exchanger connected to a heat sink. Main results show that the system should be designed to meet a cooling power of 42W.m⁻² and a desiccant rate of 45 g_H2O.h⁻¹. In a second time, a parametric study of comfort issues and system performances has been achieved on a more realistic system (that includes a chilled ceiling) under different operating conditions. It enables an estimation of an acceptable range of operating conditions. This preliminary study is intended to provide useful information for the system design.

Keywords: Dehumidification, nodal calculation, radiant cooling panel, system sizing.

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Authors: Muritala Babatunde Hassan

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In the contemporary global political economy, foreign direct investment (FDI) is gaining currency on daily basis. Notably, the end of the Cold War has brought about the dominance of neoliberal ideology with its mantra of private-sector-led economy. As such, nation-states now see FDI attraction as an important element in their approach to national development. Governments and policy makers are preoccupying themselves with unraveling the best strategies to not only attract more FDI but also to attain the desired socio-economic development status. In Nigeria, the perceived development potentials of FDI have brought about aggressive hunt for foreign investors, most especially since transition to civilian rule in May 1999. Series of liberal and market oriented strategies are being adopted not only to attract foreign investors but largely to stimulate private sector participation in the economy. It is on this premise that this study interrogates the politics of FDI attraction for domestic development in Nigeria between 1999 and 2014, with the ultimate aim of examining the nexus between regime type and the ability of a state to attract and benefit from FDI. Building its analysis within the framework of institutional utilitarianism, the study posits that the essential FDI strategies for achieving the greatest happiness for the greatest number of Nigerians are political not economic. Both content analysis and descriptive survey methodology were employed in carrying out the study. Content analysis involves desk review of literatures that culminated in the development of the study’s conceptual and theoretical framework of analysis. The study finds no significant relationship between transition to democracy and FDI inflows in Nigeria, as most of the attracted investments during the period of the study were market and resource seeking as was the case during the military regime, thereby contributing minimally to the socio-economic development of the country. It is also found that the country placed much emphasis on liberalization and incentives for FDI attraction at the neglect of improving the domestic investment environment. Consequently, poor state of infrastructure, weak institutional capability and insecurity were identified as the major factors seriously hindering the success of Nigeria in exploiting FDI for domestic development. Given the reality of the currency of FDI as a vector of economic globalization and that Nigeria is trailing the line of private-sector-led approach to development, it is recommended that emphasis should be placed on those measures aimed at improving the infrastructural facilities, building solid institutional framework, enhancing skill and technological transfer and coordinating FDI promotion activities by different agencies and at different levels of government.

Keywords: Foreign capital, politics, socio-economic development, FDI attraction strategies, Redemocratization.

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Authors: Renata Martins Pacheco, João Claro

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Wildfires are becoming an increasing concern worldwide, causing substantial social, economic, and environmental disruptions. This situation is especially relevant in Mediterranean-climate regions, present in all the five continents of the world, in which fire is not only a natural component of the environment but also perhaps one of the most important evolutionary forces. The rise in wildfire occurrences and their associated impacts suggests the need for identifying knowledge gaps and enhancing the basis of scientific evidence on how managers and policymakers may act effectively to address them. Considering that the main goal of a systematic map is to collate and catalog a body of evidence to describe the state of knowledge for a specific topic, it is a suitable approach to be used for this purpose. In this context, the aim of this study is to systematically map the research trends in wildfire management practices in Mediterranean-climate regions. A total of 201 wildfire management studies were analyzed and systematically mapped in terms of their: Year of publication; Place of study; Scientific outlet; Research area (Web of Science) or Research field (Scopus); Wildfire phase; Central research topic; Main objective of the study; Research methods; and Main conclusions or contributions. The results indicate that there is an increasing number of studies being developed on the topic (most from the last 10 years), but more than half of them are conducted in few Mediterranean countries (60% of the analyzed studies were conducted in Spain, Portugal, Greece, Italy or France), and more than 50% are focused on pre-fire issues, such as prevention and fuel management. In contrast, only 12% of the studies focused on “Economic modeling” or “Human factors and issues,” which suggests that the triple bottom line of the sustainability argument (social, environmental, and economic) is not being fully addressed by fire management research. More than one-fourth of the studies had their objective related to testing new approaches in fire or forest management, suggesting that new knowledge is being produced on the field. Nevertheless, the results indicate that most studies (about 84%) employed quantitative research methods, and only 3% of the studies used research methods that tackled social issues or addressed expert and practitioner’s knowledge. Perhaps this lack of multidisciplinary studies is one of the factors hindering more progress from being made in terms of reducing wildfire occurrences and their impacts.

Keywords: Management Mediterranean-climate regions, policy, wildfire.

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Authors: Dinara F. Gaynutdinova, Vladimir Ya Modorsky, Nikolay A. Shevelev

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The problem under research is that of unpredictable modes occurring in two-stage centrifugal hydraulic pump as a result of hydraulic processes caused by vibrations of structural components. Numerical, analytical and experimental approaches are considered. A hypothesis was developed that the problem of unpredictable pressure decrease at the second stage of centrifugal pumps is caused by cavitation effects occurring upon vibration. The problem has been studied experimentally and theoretically as of today. The theoretical study was conducted numerically and analytically. Hydroelastic processes in dynamic “liquid – deformed structure” system were numerically modelled and analysed. Using ANSYS CFX program engineering analysis complex and computing capacity of a supercomputer the cavitation parameters were established to depend on vibration parameters. An influence domain of amplitudes and vibration frequencies on concentration of cavitation bubbles was formulated. The obtained numerical solution was verified using CFM program package developed in PNRPU. The package is based on a differential equation system in hyperbolic and elliptic partial derivatives. The system is solved by using one of finite-difference method options – the particle-in-cell method. The method defines the problem solution algorithm. The obtained numerical solution was verified analytically by model problem calculations with the use of known analytical solutions of in-pipe piston movement and cantilever rod end face impact. An infrastructure consisting of an experimental fast hydro-dynamic processes research installation and a supercomputer connected by a high-speed network, was created to verify the obtained numerical solutions. Physical experiments included measurement, record, processing and analysis of data for fast processes research by using National Instrument signals measurement system and Lab View software. The model chamber end face oscillated during physical experiments and, thus, loaded the hydraulic volume. The loading frequency varied from 0 to 5 kHz. The length of the operating chamber varied from 0.4 to 1.0 m. Additional loads weighed from 2 to 10 kg. The liquid column varied from 0.4 to 1 m high. Liquid pressure history was registered. The experiment showed dependence of forced system oscillation amplitude on loading frequency at various values: operating chamber geometrical dimensions, liquid column height and structure weight. Maximum pressure oscillation (in the basic variant) amplitudes were discovered at loading frequencies of approximately 1,5 kHz. These results match the analytical and numerical solutions in ANSYS and CFM.

Keywords: Computing experiment, hydroelasticity, physical experiment, vibration.

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Authors: Mustafa M. Donma, Orkide Donma, Savas Guzel

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Iron is physiologically essential. However, it also participates in the catalysis of free radical formation reactions. Its deficiency is associated with amplified health risks. This trace element establishes some links with another physiological process related to cell death, apoptosis. Both iron deficiency and iron overload are closely associated with apoptosis. Soluble tumor necrosis factor-like weak inducer of apoptosis (sTWEAK) has the ability to trigger apoptosis and plays a dual role in the physiological versus pathological inflammatory responses of tissues. The aim of this study was to investigate the status of these parameters as well as the associations among them in children with obesity, a low-grade inflammatory state. The study was performed on groups of children with normal body mass index (N-BMI) and obesity. 43 children were included in each group. Based upon age- and sex-adjusted BMI percentile tables prepared by the World Health Organization, children whose values varied between 85 and 15 were included in N-BMI group. Children, whose BMI percentile values were between 99 and 95, comprised obese (OB) group. Institutional ethical committee approval and informed consent forms were taken prior to the study. Anthropometric measurements (weight, height, waist circumference, hip circumference, head circumference, neck circumference) and blood pressure values (systolic blood pressure and diastolic blood pressure) were recorded. Routine biochemical analyses, including serum iron, total iron binding capacity (TIBC), transferrin saturation percent (Tf Sat %) and ferritin, were performed. sTWEAK levels were determined by enzyme-linked immunosorbent assay. study data were evaluated using appropriate statistical tests performed by the statistical program SPSS. Serum iron levels were 91 ± 34 mcrg/dl and 75 ± 31 mcrg/dl in N-BMI and OB children, respectively. The corresponding values for TIBC, Tf Sat %, ferritin were 265 mcrg/dl vs. 299 mcrg/dl, 37.2 ± 19.1% vs. 26.7 ± 14.6%, and 41 ± 25 ng/ml vs 44 ± 26 ng/ml. In N-BMI and OB groups, sTWEAK concentrations were measured as 351 ng/L and 325 ng/L, respectively (p > 0.05). Correlation analysis revealed significant associations between sTWEAK levels and iron related parameters (p < 0.05) except ferritin. In conclusion, iron contributes to apoptosis. Children with iron deficiency have decreased apoptosis rate in comparison with that of healthy children. sTWEAK is an inducer of apoptosis. OB children had lower levels of both iron and sTWEAK. Low levels of sTWEAK are associated with several types of cancers and poor survival. Although iron deficiency state was not observed in this study, the correlations detected between decreased sTWEAK and decreased iron as well as Tf Sat % values were valuable findings, which point out decreased apoptosis. This may induce a proinflammatory state, potentially leading to malignancies in the future lives of OB children.

Keywords: Apoptosis, children, iron-related parameters, obesity, soluble tumor necrosis factor-like weak inducer of apoptosis.

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Authors: Melis Inalpulat, Levent Genc

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Land Use Land Cover (LULC) changes due to human activities and natural causes have become a major environmental concern. Assessment of temporal remote sensing data provides information about LULC impacts on environment. Land Surface Temperature (LST) is one of the important components for modeling environmental changes in climatological, hydrological, and agricultural studies. In this study, LULC changes (September 7, 1984 and July 8, 2014) especially in agricultural lands together with population changes (1985-2014) and LST status were investigated using remotely sensed and census data in South Marmara Watershed, Turkey. LULC changes were determined using Landsat TM and Landsat OLI data acquired in 1984 and 2014 summers. Six-band TM and OLI images were classified using supervised classification method to prepare LULC map including five classes including Forest (F), Grazing Land (G), Agricultural Land (A), Water Surface (W), Residential Area-Bare Soil (R-B) classes. The LST image was also derived from thermal bands of the same dates. LULC classification results showed that forest areas, agricultural lands, water surfaces and residential area-bare soils were increased as 65751 ha, 20163 ha, 1924 ha and 20462 ha respectively. In comparison, a dramatic decrement occurred in grazing land (107985 ha) within three decades. The population increased 29% between years 1984-2014 in whole study area. Along with the natural causes, migration also caused this increase since the study area has an important employment potential. LULC was transformed among the classes due to the expansion in residential, commercial and industrial areas as well as political decisions. In the study, results showed that agricultural lands around the settlement areas transformed to residential areas in 30 years. The LST images showed that mean temperatures were ranged between 26-32°C in 1984 and 27-33°C in 2014. Minimum temperature of agricultural lands was increased 3°C and reached to 23°C. In contrast, maximum temperature of A class decreased to 41°C from 44°C. Considering temperatures of the 2014 R-B class and 1984 status of same areas, it was seen that mean, min and max temperatures increased by 2°C. As a result, the dynamism of population, LULC and LST resulted in increasing mean and maximum surface temperatures, living spaces/industrial areas and agricultural lands.

Keywords: Census data, landsat, land surface temperature (LST), land use land cover (LULC).

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Authors: Agâh Tuğrul Korucu, Ismail Fatih Yavuzaslan, Lale Toraman

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Nowadays, thanks to development of technology, integration of technology into teaching and learning activities is spreading. Increasing technological literacy which is one of the expected competencies for individuals of 21st century is associated with the effective use of technology in education. The most important factor in effective use of technology in education institutions is ICT teachers. The concept of computer assisted instruction (CAI) refers to the utilization of information and communication technology as a tool aided teachers in order to make education more efficient and improve its quality in the process of educational. Teachers can use computers in different places and times according to owned hardware and software facilities and characteristics of the subject and student in CAI. Analyzing teachers’ use of computers in education is significant because teachers are the ones who manage the course and they are the most important element in comprehending the topic by students. To accomplish computer-assisted instruction efficiently is possible through having positive attitude of teachers. Determination the level of knowledge, attitude and behavior of teachers who get the professional knowledge from educational faculties and elimination of deficiencies if any are crucial when teachers are at the faculty. Therefore, the aim of this paper is to identify ICT teachers' attitudes toward computer-assisted instruction in terms of different variables. Research group consists of 200 prospective ICT teachers studying at Necmettin Erbakan University Ahmet Keleşoğlu Faculty of Education CEIT department. As data collection tool of the study; “personal information form” developed by the researchers and used to collect demographic data and "the attitude scale related to computer-assisted instruction" are used. The scale consists of 20 items. 10 of these items show positive feature, while 10 of them show negative feature. The Kaiser-Meyer-Olkin (KMO) coefficient of the scale is found 0.88 and Barlett test significance value is found 0.000. The Cronbach’s alpha reliability coefficient of the scale is found 0.93. In order to analyze the data collected by data collection tools computer-based statistical software package used; statistical techniques such as descriptive statistics, t-test, and analysis of variance are utilized. It is determined that the attitudes of prospective instructors towards computers do not differ according to their educational branches. On the other hand, the attitudes of prospective instructors who own computers towards computer-supported education are determined higher than those of the prospective instructors who do not own computers. It is established that the departments of students who previously received computer lessons do not affect this situation so much. The result is that; the computer experience affects the attitude point regarding the computer-supported education positively.

Keywords: Attitude, computer based instruction, information and communication technologies, technology based instruction, teacher candidate.

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Authors: A. Schuchter, M. Promegger

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The outbreak of the COVID-19 pandemic has shown us that online education is so much more than just a cool feature for teachers – it is an essential part of modern teaching. In online math teaching, it is common to use tools to share screens, compute and calculate mathematical examples, while the students can watch the process. On the other hand, flipped classroom models are on the rise, with their focus on how students can gather knowledge by watching videos and on the teacher’s use of technological tools for information transfer. This paper proposes a co-educational teaching approach for coding and engineering subjects with the help of drone-building to spark interest in technology and create a platform for knowledge transfer. The project combines aspects from mathematics (matrices, vectors, shaders, trigonometry), physics (force, pressure and rotation) and coding (computational thinking, block-based programming, JavaScript and Python) and makes use of collaborative-shared 3D Modeling with clara.io, where students create mathematics knowhow. The instructor follows a problem-based learning approach and encourages their students to find solutions in their own time and in their own way, which will help them develop new skills intuitively and boost logically structured thinking. The collaborative aspect of working in groups will help the students develop communication skills as well as structural and computational thinking. Students are not just listeners as in traditional classroom settings, but play an active part in creating content together by compiling a Handbook of Knowledge (called “open book”) with examples and solutions. Before students start calculating, they have to write down all their ideas and working steps in full sentences so other students can easily follow their train of thought. Therefore, students will learn to formulate goals, solve problems, and create a ready-to use product with the help of “reverse engineering”, cross-referencing and creative thinking. The work on drones gives the students the opportunity to create a real-life application with a practical purpose, while going through all stages of product development.

Keywords: Flipped classroom, co-creational education, coding, making, drones, co-education, ARCS-model, problem-based learning.

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Authors: Mustafa M. Donma, Orkide Donma

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Metabolisms of macrominerals, those of calcium, phosphorus and magnesium, are closely associated with the metabolism of vitamin D. Particularly magnesium, the second most abundant intracellular cation, is related to biochemical and metabolic processes in the body, such as those of carbohydrates, proteins and lipids. The status of each mineral was investigated in obesity to some extent. Their products and ratios may possibly give much more detailed information about the matter. The aim of this study is to investigate possible relations between each macromineral and some obesity-related parameters. This study was performed on 235 children, whose ages were between 06-18 years. Aside from anthropometric measurements, hematological analyses were performed. TANITA body composition monitor using bioelectrical impedance analysis technology was used to establish some obesity-related parameters including basal metabolic rate (BMR), total fat, mineral and muscle masses. World Health Organization body mass index (BMI) percentiles for age and sex were used to constitute the groups. The values above 99^th percentile were defined as morbid obesity. Those between 95^th and 99^th percentiles were included into the obese group. The overweight group comprised of children whose percentiles were between 95 and 85. Children between the 85^th and 15^th percentiles were defined as normal. Metabolic syndrome (MetS) components (waist circumference, fasting blood glucose, triacylglycerol, high density lipoprotein cholesterol, systolic pressure, diastolic pressure) were determined. High performance liquid chromatography was used to determine Vitamin D status by measuring 25-hydroxy cholecalciferol (25-hydroxy vitamin D₃, 25(OH)D). Vitamin D values above 30.0 ng/ml were accepted as sufficient. SPSS statistical package program was used for the evaluation of data. The statistical significance degree was accepted as p < 0.05. The important points were the correlations found between vitamin D and magnesium as well as phosphorus (p < 0.05) that existed in the group with normal BMI values. These correlations were lost in the other groups. The ratio of phosphorus to magnesium was even much more highly correlated with vitamin D (p < 0.001). The negative correlation between magnesium and total fat mass (p < 0.01) was confined to the MetS group showing the inverse relationship between magnesium levels and obesity degree. In this group, calcium*magnesium product exhibited the highest correlation with total fat mass (p < 0.001) among all groups. Only in the MetS group was a negative correlation found between BMR and calcium*magnesium product (p < 0.05). In conclusion, magnesium is located at the center of attraction concerning its relationships with vitamin D, fat mass and MetS. The ratios and products derived from macrominerals including magnesium have pointed out stronger associations other than each element alone. Final considerations have shown that unique correlations of magnesium as well as calcium*magnesium product with total fat mass have drawn attention particularly in the MetS group, possibly due to the derangements in some basic elements of carbohydrate as well as lipid metabolism.

Keywords: Macrominerals, metabolic syndrome, pediatric obesity, vitamin D.

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Authors: D. Goustouridis, A. Sideris, I. Sdrolias, G. Loizos, N.-Alexander Tatlas, S. M. Potirakis

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Both daily and long-term management of a heavy-duty vehicles and construction machinery fleet is an extremely complicated and hard to solve issue. This is mainly due to the diversity of the fleet vehicles – machinery, which concerns not only the vehicle types, but also their age/efficiency, as well as the fleet volume, which is often of the order of hundreds or even thousands of vehicles/machineries. In the present paper we present “InteligentLogger”, a holistic heavy-duty fleet management system covering a wide range of diverse fleet vehicles. This is based on specifically designed hardware and software for the automated vehicle health status and operational cost monitoring, for smart maintenance. InteligentLogger is characterized by high adaptability that permits to be tailored to practically any heavy-duty vehicle/machinery (of different technologies -modern or legacy- and of dissimilar uses). Contrary to conventional logistic systems, which are characterized by raised operational costs and often errors, InteligentLogger provides a cost-effective and reliable integrated solution for the e-management and e-maintenance of the fleet members. The InteligentLogger system offers the following unique features that guarantee successful heavy-duty vehicles/machineries fleet management: (a) Recording and storage of operating data of motorized construction machinery, in a reliable way and in real time, using specifically designed Internet of Things (IoT) sensor nodes that communicate through the available network infrastructures, e.g., 3G/LTE; (b) Use on any machine, regardless of its age, in a universal way; (c) Flexibility and complete customization both in terms of data collection, integration with 3rd party systems, as well as in terms of processing and drawing conclusions; (d) Validation, error reporting & correction, as well as update of the system’s database; (e) Artificial intelligence (AI) software, for processing information in real time, identifying out-of-normal behavior and generating alerts; (f) A MicroStrategy based enterprise BI, for modeling information and producing reports, dashboards, and alerts focusing on vehicles– machinery optimal usage, as well as maintenance and scraping policies; (g) Modular structure that allows low implementation costs in the basic fully functional version, but offers scalability without requiring a complete system upgrade.

Keywords: E-maintenance, predictive maintenance, IoT sensor nodes, cost optimization, artificial intelligence, heavy-duty vehicles.

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